Dry Bean Sensitivity to Group 15 Herbicides Applied Preemergence
Bibliographic record
Abstract
Field experiments (4 in total) were conducted in 2016 and 2017 in southwestern Ontario to compare the sensitivity of dry bean to four Group 15 herbicides applied preemergence (PRE). At 4 weeks after emergence (WAE), pethoxamid, S-metolachlor, dimethenamid-P and pyroxasulfone applied PRE at the 2X rate caused 5%, 9%, 9% and 14% visible injury in adzuki bean, 2%, 2%, 2% and 3% visible injury in kidney bean, 6%, 4%, 5% and 4% visible injury in small red Mexican (SRM) bean, and 9%, 6%, 8% and 9% visible injury in white bean, respectively. Pyroxasulfone reduced adzuki bean shoot biomass (m-1 row) 42% and height 12%. However, the other Group 15 herbicides did not reduce shoot biomass and height of adzuki bean. Kidney bean shoot biomass and height were not adversely affected by the Group 15 herbicides evaluated. S-metolachlor caused no adverse effect on SRM bean dry weight or height, but pethoxamid, dimethenamid-P and pyroxasulfone at the 2X rate reduced dry weight 26%, 28% and 28% and height 7%, 7% and 7% in SRM bean, respectively. Pethoxamid, S-metolachlor, dimethenamid-P, and pyroxasulfone applied PRE at the 2X rate reduced white bean dry weight 50%, 37%, 47% and 43% and height 16%, 10%, 16% and 15% in white bean, respectively. Pyroxasulfone (2X rate), applied PRE, reduced bean stand count and seed yield 12% and 7%, respectively. However, pethoxamid, S-metolachlor, and dimethenamid-P, applied PRE caused no decrease in stand count and seed yield of dry beans evaluated. In general, kidney and SRM bean are most tolerant, white bean is intermediate, and adzuki bean is most sensitive to Group 15 herbicides applied PRE.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".